Intern - Software Engineer, Cloud Technology Architecture

Akamai

5h•Remote

About The Position

Do you enjoy solving real-world problems at the scale of the Internet? Are you excited about combining data analysis, systems thinking, and machine learning to improve the performance and efficiency of large-scale infrastructure? Join Our Cloud Technology & Architecture Team! Akamai's Cloud Technology Architecture team builds the data models, algorithms, and tools that guide how Akamai's global edge platform is operated and evolved. Our work improves cache efficiency, optimizes traffic placement, reduces infrastructure costs, and helps the network operate sustainably. We are looking for an intern to develop data-driven analysis, modeling, and optimization approaches that improve performance, cost efficiency, and operational visibility across Akamai's global content delivery network. You will work with stakeholders across Capacity Engineering, Network Engineering, and Data Science teams to turn large-scale operational data into actionable insights and automation. Depending on your experience level, projects may range from building data pipelines and analysis tools to developing advanced modeling and optimization solutions. Help shape the future of the Internet This role requires you to be available 40-hours per week for the duration of Akamai's summer internship program (May 26th-August 14th). In this role, you will work on data-driven optimization and intelligent automation for Akamai's edge infrastructure. You will collaborate with engineers and researchers on to influence how capacity deployments, traffic management, and performance delivery to customers worldwide. As a Cloud Technology Architecture Intern, you will be responsible for:

Requirements

Be pursuing a Bachelor's, Master's, or PhD in Computer Science, Electrical Engineering, Data Science, or a related field.
Have experience programming in Python, Java, C++, Go, or a similar language, and experience working with data or building analytical tools.
Have experience working in Linux/Unix environments and familiarity with optimization tools (e.g., CPLEX, Gurobi) or modern AI-assisted development tools.
Have a foundation in computer science fundamentals such as data structures, algorithms, systems, networks, databases, or basic machine learning/statistics concepts.
Have a strong foundation in computer science fundamentals such as data structures, algorithms, systems, networks, databases, or basic machine learning/statistics concepts.

Responsibilities

Building data pipelines, tools, or analysis workflows to process large-scale network and cache data.
Analyzing system behavior to identify performance, efficiency, and cost improvement opportunities.
Developing models, simulations, or algorithms to improve cache policies, traffic placement, or infrastructure allocation decisions.
Building prototypes using machine learning or AI techniques to automate tasks such as performance analysis, anomaly detection, or operational insights.
Presenting findings and recommendations that support capacity planning, sustainability (e.g., carbon-aware decisions), and cost optimization.